搜索医学 AI 论文与资源

The PhysioNet/CinC Challenge 2012 dataset contains ICU time-series records used for mortality prediction and patient-specific outcome modeling. It remains a useful benchmark for clinical time-series modeling, missingness-aware learning, and early warning model development.

AMOS is an abdominal multi-organ segmentation benchmark with CT and MRI cases for evaluating versatile medical image segmentation models. It supports abdominal organ segmentation, modality-general segmentation, and benchmarking of robust 3D segmentation methods.

REFUGE is a retinal fundus imaging challenge dataset for glaucoma assessment. It supports glaucoma classification, optic disc and cup segmentation, fovea localization, and fair comparison of ophthalmology AI methods on color fundus photographs.

The RSNA Pneumonia Detection Challenge dataset is a chest radiograph benchmark for detecting pneumonia-related lung opacities. It supports object detection, chest X-ray classification, localization, and radiology AI evaluation under a competition framework.

ACDC is a cardiac MRI dataset for automated cardiac diagnosis and segmentation. It supports left and right ventricular segmentation, myocardium segmentation, cardiac function quantification, and evaluation of robust cardiac image analysis methods.

CAMELYON17 is a digital pathology dataset for detecting breast cancer metastases in lymph node whole-slide images across multiple centers. It supports pathology classification, metastasis detection, weakly supervised learning, and domain generalization in histopathology AI.

BraTS 2024 provides multimodal brain MRI data and expert annotations for brain tumor segmentation and related tumor subregion analysis. It is a major benchmark for glioma segmentation, radiology AI, and robust multimodal MRI segmentation methods.